TL;DR: Twelve months ago, AI agents looked like a new species that invalidated everything we knew. Then Anthropic decomposed agents into Brain, Hands, and Session — and out fell event sourcing, sta...

TL;DR: When a small model claims 128K context, it means the positional encoding goes that far. It doesn’t mean the model can actually use it. Most on-device models have an effective context of 8-16...

TL;DR: Last month I wrote about three paths to local AI (BitNet, quantization, engine optimization). Gemma 4 just added a fourth: architecture efficiency. Here’s how all four fit together — and wha...

TL;DR: AI agent security maps 1:1 to patterns we solved decades ago — firewalls, IDS, DPI, defense in depth. The defense playbook is ready. The real bottleneck? Agent Identity. Until agents have st...

TL;DR: Eric Schmidt says universities should teach AI tools from day one. He’s confusing education with training. Universities exist to build judgment, not tool proficiency. That distinction matter...

TL;DR: Musk frames Optimus as an answer to US-China competition. But the real question isn’t which country builds more robots — it’s who captures the value when robots replace workers. He dressed u...

“AI handles breadth, humans handle depth.” Translate it to the job market: a ten-layer pyramid compressed to three. Only the top remains. The Math Terence Tao on his AI experience: auxiliary task...

Every few months, someone warns me: “The AI window is closing. If you don’t move now, you’ll be left behind.” It’s compelling. It also doesn’t hold up. The Contradiction If AI keeps getting bett...

TL;DR: Stop asking “can I trust AI?” — ask “can I redo this if it goes wrong?” That one question tells you what to delegate. Everyone’s debating whether AI is “ready” for real work. Karpathy say...

TL;DR: Everyone’s talking about AI replacing white-collar jobs. Few are asking: where do those displaced workers go, and what happens when they get there? A two-wave impact model suggests the real ...